Archive for the ‘Database Management’ Category
Image source: www.java.sun.com
Creating web applications is as complex as writing a thesis paper or a dissertation. It does not only necessitate quite a tedious amount of effort to perfect the function of the program but also demands one stable thing from the user: internet association.
Whenever a program is being written, it takes several factors in deliberation but the most important of them is the user-interface. It is imperative that the application’s interface is easy to understand, lest it will not be used as it was intended to be so.
Using a atypical office text created raises an issue on standards compliance, moving the evasive issue of file partaking and association. What must be noticed is that these browser applications are used by accessing the internet through the remote servers. It is threatening however, for the document, if the connection is suddenly lost or interrupted. Chances are, the document being programmed online will be lost and inferior, irretrievable.
This kind of disadvantage poses a threat to the survival of the web applications, hence, companies such as Google have made preliminary solutions to this problem. However, for now, only prototypes have been developed to repress the threat raised by this problem. Just like so, Google has created Google Gears—a beta display place that aims to improve the usability of web applications.
uk.oracle.com
This is a proven strategy in helping you manage the database growth in your organization. If you classify data according to value, you will find that highly available ones need to be left in production server, while those that are less valuable can be moved to lower storage tiers.
With data archiving functions, your organization can make and deploy policies that are consistent for storing, securing, and managing data. There will be a good result of availability and improved application performance that will reallocate inactive files from production database into a more secure offline or online data archive. The organization will just maintain access though the application layer of the native enterprise – it will ensure seamless access of data for long term reporting requirements.
wiki.liferay.com
If the data growth is unchecked, it will affect all other areas of the company and also make it impossible for full utilization of SCM, ERP, and CRM applications. This will potentially impact business performance and decrease productivity.
If there are large data volumes, it will also slow down the reporting process and application response time. This will have a net effect of limited business decisions especially during the quarter and year-end close. If you will maintain large database applications, it will add to the cost, risk and complexity of the business. There will also be more time spent to perform routine maintenance and back-up activities.
www.cbtplanet.com
Unlike file and e-mail servers, database applications require multiple copies in the production system. There should be versions for training, QA, patch, test, and a possible stand-by copy for purposes of disaster recovery. As production in the database grows, so will all copies, as it will consume large storage quantities.
Also, the government and other regulatory bodies are pushing for data retention. Healthcare data for example, needs to range from 10 years of patient records up to permanent storage of data for deaths and births. Some banks also need to retain data for 5-7 years to make sure that there are proper operational and financial records of businesses. Without proper data management strategy, the company will carry a huge burden since failure to produce records is no longer considered as a defensible strategy in court litigations.
www.chemware.com
Increase in compliance for regulations and growing data volumes will require companies to further evaluate their strategies for data management as well as implement scalable solutions to solve the challenges of today. The company’s data management also has to integrate the existing application infrastructure that will provide the means of managing data growth while at the same time maintain referential integrity of application.
For example, e-business applications in companies have given them the capturing, analyzing, and retaining ability for huge amounts of data regarding its suppliers, customers or business transactions. Furthermore, there is high pressure on IT systems to capture millions of data and store it efficiently.